alterlab-pyhealth

alterlab-pyhealth is a skill for Claude Code from AlterLab-IEU/AlterLab-Academic-Skills. It costs 117 tokens per session (4,817 once invoked), scanned A, original, MIT.

A toolkit for building machine-learning models from healthcare data, such as electronic health records, medical codes, and signals like ECG or EEG. PyHealth is a Python library designed for these clinical prediction tasks.

In plain words
What is it for?
Use it to predict outcomes such as death or hospital readmission, recommend drugs, process medical coding systems, and work with selected physiological signals.
Why use it?
It gives healthcare projects task-specific data handling, models, and evaluation methods instead of requiring developers to build them from general-purpose machine-learning tools.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the alterlab-clinical-research plugin — 7 skills shipped together

Good fit Use it to predict outcomes such as death or hospital readmission, recommend drugs, process medical coding systems, and work with selected physiological signals.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alterlab-ieu/alterlab-academic-skills/alterlab-pyhealth
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-pyhealth
Clone the repo
git clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-Skills

Made for: Claude Code.

Or install alterlab-clinical-research, the plugin that ships this one along with the rest of its 7 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for alterlab-pyhealth

README.md
[![agentmods](https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pyhealth/github.svg)](https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pyhealth)
Your own site
<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pyhealth"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pyhealth/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for alterlab-pyhealth

Your own site · 80×15
<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pyhealth"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pyhealth.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 117 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,817 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00117 $0.04817
Opus 5 $0.00059 $0.02409
Sonnet 5 $0.00023 $0.00963
Haiku 4.5 $0.00012 $0.00482

Measured 12d ago against content hash 991a64ba28e7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

alterlab-pyhealth scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/clinical-research/alterlab-pyhealth/SKILL.md · 510 lines

How it starts

The opening of the file, as written. The whole thing — 510 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PyHealth: Healthcare AI Toolkit

Overview

PyHealth is a comprehensive Python library for healthcare AI that provides specialized tools, models, and datasets for clinical machine learning. Use this skill when developing healthcare prediction models, processing clinical data, working with medical coding systems, or deploying AI solutions in healthcare settings.

Version gotcha (read first). This skill targets PyHealth 2.x (pin pyhealth==2.0.1). The 2.0 rewrite changed the API in ways the wider web (and pre-2024 tutorials) get wrong:

  • Tasks are classes you instantiate, e.g. MortalityPredictionMIMIC4(), DrugRecommendationMIMIC3()not the old snake-case mortality_prediction_mimic4_fn functions. Pass the instance to dataset.set_task(task).
  • Datasets take an explicit tables=[...] list (e.g. tables=["diagnoses_icd", "procedures_icd", "prescriptions"]).
  • Models require label_key= in addition to feature_keys= and mode=. Common feature keys for EHR tasks are "conditions", "procedures", "drugs".
  • Metric names have no _score suffix: pr_auc, roc_auc, f1; multilabel/drug-rec use the *_samples family (jaccard_samples, f1_samples, pr_auc_samples, ddi). Pass metrics=[...] to the Trainer constructor, and monitor= one of those names.
  • 2.0.1 requires Python 3.12 or 3.13 (>=3.12,<3.14). When unsure of a class/arg name, check the current source rather than trusting older snippets.

When to Use This Skill

Invoke this skill when:

  • Working with healthcare datasets: MIMIC-III, MIMIC-IV, eICU, OMOP, sleep EEG data, medical images
  • Clinical prediction tasks: Mortality prediction, hospital readmission, length of stay, drug recommendation
  • Medical coding: Translating between ICD-9/10, NDC, RxNorm, ATC coding systems
  • Processing clinical data: Sequential events, physiological signals, clinical text, medical images
  • Implementing healthcare models: RETAIN, SafeDrug, GAMENet, StageNet, Transformer for EHR
  • Evaluating clinical models: Fairness metrics, calibration, interpretability, uncertainty quantification

Read the full file on GitHub · 510 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 510 lines · 117 tokens per session scan A 991a64ba28e7

Subscribe to this mod's changes

alterlab-pyhealth is a skill published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (66 stars, last pushed 7d ago), licensed MIT. It adds 117 tokens to every session and 4,817 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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